Testing method for myocardial tissue biomimetic unit model

Abstract

The present invention provides a testing method for a bionic myocardial tissue unit model, relating to the technical field of bionic model testing. The method includes obtaining big data on myocardial tissue measurements and establishing a digital myocardial tissue model based on contractile performance based on the bionic myocardial tissue unit model; obtaining contractile performance parameters of the bionic myocardial tissue unit model and performing contractility matching analysis in combination with the digital myocardial tissue model to generate contractility matching verification information; obtaining mechanical performance parameters of the bionic myocardial tissue unit model and performing mechanical performance matching analysis in combination with the digital myocardial tissue model to generate mechanical matching verification information; and extracting electrocardiogram (ECG) activity data from the big data on myocardial tissue measurements and combining it with the ECG activity information of the bionic myocardial tissue unit model to generate ECG matching verification information. By utilizing the big data on myocardial tissue measurements to conduct multiple verification tests, this method effectively ensures the reliable working performance of the bionic myocardial tissue unit model.

Description

Technical Field

[0001] The present invention relates to the technical field of bionic model testing, and in particular to a testing method for a myocardial tissue bionic unit model. Background Art

[0002] With advancements in medical technology, treatments for heart diseases are becoming increasingly advanced and comprehensive. For cases where the myocardium is damaged and unable to recover functionally, it's possible to provide a bionic alternative that can achieve better myocardial function.

[0003] Currently, the development of bionic myocardial tissue models is becoming increasingly advanced, gradually producing model structures that can completely replace the entire myocardium's functions, providing the possibility of myocardial replacement. Given the different movements of myocardial tissue under normal circumstances, achieving its motion performance is relatively difficult. Furthermore, verifying the reliability and performance of the designed bionic myocardial tissue models has become a key challenge in the current research and development of bionic myocardial tissue models.

[0004] Therefore, designing a testing method for the myocardial tissue bionic unit model and conducting verification tests in multiple aspects by utilizing the measurement big data of myocardial tissue to effectively ensure the reliable working performance of the myocardial tissue bionic unit model is an urgent problem to be solved. Summary of the Invention

[0005] The purpose of the present invention is to provide a testing method for a myocardial tissue bionic unit model, by acquiring big data of myocardial tissue measurements to establish a digital model of myocardial tissue for comparative verification testing with the myocardial tissue bionic unit model, and by matching and verifying the contractile performance, mechanical properties and electrocardiographic activity data of the myocardial tissue bionic unit model to determine its performance and functionality in many aspects, thereby effectively ensuring the performance of the myocardial tissue bionic unit model. At the same time, a systematic method for performance testing of the myocardial tissue bionic unit model is formed, thereby improving the efficiency of performance verification testing of the myocardial tissue bionic unit model.

[0006] In a first aspect, the present invention provides a testing method for a myocardial tissue bionic unit model, comprising: obtaining myocardial tissue measurement big data, extracting myocardial tissue contraction performance test data and myocardial tissue scanning data, and establishing a myocardial tissue digital model based on contraction performance according to the myocardial tissue bionic unit model; obtaining contraction performance parameters of the myocardial tissue bionic unit model, and performing contractility matching analysis in combination with the myocardial tissue digital model to form contractility matching verification information; obtaining mechanical performance parameters of the myocardial tissue bionic unit model based on the contractility matching verification information, and performing mechanical performance matching analysis in combination with the myocardial tissue digital model to form mechanical matching verification information; extracting electrocardiogram (ECG) activity data from the myocardial tissue measurement big data based on the mechanical matching verification information, and performing ECG activity matching analysis in combination with the ECG activity information of the myocardial tissue bionic unit model to form ECG activity matching verification information.

[0007] In the present invention, the method obtains big data of myocardial tissue measurements to establish a digital model of myocardial tissue for comparative verification testing with a myocardial tissue bionic unit model, and through separate matching verification of the contractile performance, mechanical properties and electrocardiographic activity data of the myocardial tissue bionic unit model, determines its performance and functionality in many aspects, effectively guarantees the performance of the myocardial tissue bionic unit model, and also forms a systematic method for performance testing of the myocardial tissue bionic unit model, thereby improving the efficiency of performance verification testing of the myocardial tissue bionic unit model.

[0008] As a possible implementation method, myocardial tissue measurement big data is obtained, myocardial tissue contraction performance test data and myocardial tissue scanning data are extracted, and a myocardial tissue digital model based on contraction performance is established according to the myocardial tissue bionic unit model, including: establishing a basic digital model of myocardial tissue according to the myocardial tissue scanning data and in combination with the myocardial tissue bionic unit model; performing feature extraction based on contraction performance according to the myocardial tissue contraction performance test data and in combination with the basic digital model of myocardial tissue to form model contraction performance characteristic data; using the model contraction performance characteristic data as a design indicator, adjusting the model performance of the basic digital model of myocardial tissue based on secondary development to establish a digital model of myocardial tissue.

[0009] In the present invention, a digital model of myocardial tissue that matches the myocardial tissue bionic unit model is established based on the big data of myocardial tissue measurements. Three aspects need to be considered. One is the basic data of the model. The basic data here is the basic information required to generate the digital model, such as size, structure and other information. Based on this information, a digital model can be quickly established. The other is the performance data of the model. Considering that the performance of cardiac tissue is mainly obtained through its motion information, this application mainly considers establishing the corresponding model characteristic performance by obtaining contraction performance characteristic data.

[0010] As a possible implementation method, a basic digital model of myocardial tissue is established based on myocardial tissue scanning data and combined with a myocardial tissue bionic unit model, including: collecting size contour information of the myocardial tissue bionic unit model to form target model size contour feature information; using the target model size contour feature information as a reference, extracting matching scanning information corresponding to myocardial tissue whose size contour information in the myocardial tissue scanning data matches the target model size contour feature information, and determining the matched myocardial tissue as the matching myocardial tissue; determining the average basic parameter value of different basic model parameters based on all matching scanning information; and combining the target model size contour feature information and different average basic parameter values ​​to form a basic digital model of myocardial tissue.

[0011] In the present invention, the basic digital model of myocardial tissue primarily captures contour data, such as the size and structure, of myocardial tissue from measurement data. Considering that myocardial tissue is a biological tissue with certain individual differences, the bionic unit model of myocardial tissue inevitably has different applicability to different populations. Therefore, when establishing the basic digital model of myocardial tissue, it is necessary to consider the impact of individual differences on the measurement data to avoid inaccurate results from subsequent validation tests caused by data that does not match the bionic unit model of myocardial tissue. Individual differences in myocardial tissue are primarily manifested in age, and the size of myocardial tissue corresponding to individuals of different ages varies. Therefore, the dimensional contour feature information required to establish the basic digital model of myocardial tissue is clustered and acquired using the dimensional contour feature information of the bionic unit model of myocardial tissue as a reference. This reference can be a range of dimensional contour feature information based on the bionic unit model of myocardial tissue, or it can be a set of identical single parameters. Once the matching data is determined, the dimensional contour feature information of the myocardial tissue measurement data of different individuals from the clustered measurement data can be extracted. Considering the certain volatility of the feature information, the average value of the different feature information is used as the input parameter for data model establishment to better adapt to the characteristics of the corresponding population. It should be noted that the size profile information can be obtained by providing scanning information in measurement big data, such as X-rays, nuclear magnetic resonance, etc., and other important parameter information such as average density can also be obtained.

[0012] As a possible implementation method, based on the myocardial tissue contractility test data and in combination with the basic digital model of the myocardial tissue, feature extraction based on contractility performance is performed to form model contractility performance characteristic data, including: extracting different relevant contractility parameter values ​​in all matching myocardial tissues based on the myocardial tissue contractility test data, and clustering the different relevant contractility parameter values ​​to form different relevant contractility parameter sets; for different relevant contractility parameter sets, determining the corresponding average relevant contractility parameter values ​​and relevant contractility parameter ranges; and combining different average relevant contractility parameter values ​​and corresponding relevant contractility parameter ranges to form model contractility performance characteristic data.

[0013] In the present invention, the contractility of myocardial tissue can be measured using parameters such as the rate of change of ventricular pressure, the slope of the arterial pressure rise, the ejection fraction, and the isovolumetric contraction period. Therefore, when establishing the performance characteristics of an array model for a basic digital model of myocardial tissue based on measured big data, the data of different contractility parameters can be used as input. It should be noted that contractility primarily reflects the operating state and condition of myocardial tissue during movement and is a comprehensive indicator reflecting the operating performance of myocardial tissue. Therefore, basing the characteristics of the basic digital model on contractility can essentially ensure that the resulting data model has a complete performance consideration. Furthermore, due to the large amount of data, it is more reasonable to express the different contractility parameters obtained in the form of average values. Corresponding parameter ranges are also provided to provide a reasonable adjustment range reference for considering the correlation between different contractility parameters during analysis, which may affect the adjustment of other contractility parameters when adjusting a single contractility parameter.

[0014] As a possible implementation method, the model contraction performance characteristic data is used as a design indicator, and the model performance adjustment of the basic digital model of myocardial tissue is performed based on secondary development to establish a digital model of myocardial tissue, including: for the basic digital model of myocardial tissue, different average related contraction parameter values ​​are used as initial development and design targets, and different related contraction parameter ranges are used as target allowable adjustment ranges, and the secondary development model performance adjustment is performed in the following manner: the basic digital model of myocardial tissue is secondary developed according to the initial development and design targets, and if the secondary development result matches all the average related contraction parameter values, the model formed by the secondary development is determined as the digital model of myocardial tissue; if the secondary development result does not match all the average related contraction parameter values, the unmatched average related contraction parameter values ​​are adjusted within the corresponding target allowable adjustment range, so that the secondary development result matches all the average related contraction parameter values, and the model formed by the secondary development is determined as the digital model of myocardial tissue.

[0015] In the present invention, when the digital model is given functionality by the shrinkage performance parameters, the parameter data cannot be directly implemented under the original or initial digital software or model parameters. Instead, it is necessary to use the digital software or model to carry out secondary development for the shrinkage performance parameters. This secondary development mainly establishes the relationship between the multiple adjustable basic parameters of the digital model and the shrinkage performance parameters, and then autonomously optimizes the design with the shrinkage performance parameters as the target. Since the correlation between the shrinkage performance itself will be reflected through the adjustable basic parameters, it is not necessarily reasonable to initially use the average value of different shrinkage performance parameters as input. Through the optimization process of secondary development, it can be determined whether the change of the adjustable basic parameters can match all the shrinkage performance parameters. If not, adjustments can be made based on the allowed adjustment range.

[0016] As a possible implementation method, the contraction performance parameters of the myocardial tissue bionic unit model are obtained, and a contractility matching analysis is performed in combination with the myocardial tissue digital model to form contractility matching verification information, including: setting the contraction matching allowable deviation corresponding to different contraction performance parameters, and determining the bionic contraction performance parameter values ​​of the different contraction performance parameters of the myocardial tissue bionic unit model; obtaining the model contraction performance parameter values ​​corresponding to different contraction performance parameters in the myocardial tissue digital model, and performing the following matching analysis in combination with the different bionic contraction performance parameter values ​​corresponding to the myocardial tissue bionic unit model: if for all contraction performance parameters, the difference between the bionic contraction performance parameter value and the corresponding model contraction performance parameter value does not exceed the corresponding contraction matching allowable deviation, then contractility matching verification pass information is formed; if for all contraction performance parameters, the difference between the bionic contraction performance parameter value and the corresponding model contraction performance parameter value exceeds the corresponding contraction matching allowable deviation, then contractility matching verification fail information is formed.

[0017] In the present invention, the digital model of myocardial tissue determined through secondary development has contractile performance that matches big data, thus establishing comparative data that can be matched with the myocardial tissue bionic unit model for verification testing. The first verification test of the myocardial tissue bionic unit model is the contractile performance, which is a comprehensive manifestation and has a certain macroscopic nature. This matching takes into account the certain differences between the digital model of myocardial tissue and the myocardial tissue bionic unit model, so the comparative verification test is controlled by the allowable deviation. The allowable deviation can be set according to the actual situation or determined based on big data analysis.

[0018] As a possible implementation method, the mechanical performance parameters of the myocardial tissue bionic unit model are obtained according to the contractility matching verification information, and a mechanical performance matching analysis is performed in combination with the myocardial tissue digital model to form mechanical matching verification information, including: when the contractility matching verification information is contractility matching verification pass information, the bionic mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue bionic unit model are collected; the model mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue digital model are obtained, and a mechanical performance matching analysis is performed in combination with the bionic mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue bionic unit model to form mechanical matching verification information.

[0019] In the present invention, myocardial tissue movement is a process of force variation. Therefore, after confirming that contractility matching has passed verification, a matching analysis of mechanical properties is crucial and necessary to ensure that performance meets standards. This analysis can reflect the mechanical characteristics of the bionic myocardial tissue unit model. Of course, this matching analysis is performed using the data from the digital model's various mechanical performance parameters as a comparison.

[0020] As a possible implementation method, the model mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue digital model are obtained, and the mechanical performance matching analysis is performed in combination with the bionic mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue bionic unit model to form mechanical matching verification information, including: determining the model mechanical comprehensive performance value corresponding to the myocardial tissue digital model for the model mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue digital model ,in: , n is the number of different mechanical performance parameters, is an important contributing factor to the mechanical property parameter value numbered n, The model mechanical performance parameter value corresponding to the mechanical performance parameter numbered n; the bionic mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue bionic unit model are used to determine the bionic mechanical comprehensive performance value corresponding to the myocardial tissue bionic unit model ,in: , is the bionic mechanical performance parameter value corresponding to the mechanical performance parameter numbered n; the comprehensive mechanical performance value of the model and bionic mechanical comprehensive performance value :like , then the mechanical matching verification information is formed; if , then the mechanical matching verification fails. Allowable deviation for mechanical matching.

[0021] In the present invention, it should be noted that for the mechanical properties of the myocardial tissue bionic unit model, since the mechanical parameters have an inherent connection, such as stress and strain, and the transmission of force flow also has regularity and correlation on different structures, the verification test of the mechanical properties is a comprehensive comparative analysis of the mechanical performance parameters under consideration. The important contribution factors are the embodiment of the importance of different mechanical performance parameters in the verification test or in the myocardial tissue on the movement of the myocardial tissue. They can be set according to the actual situation or determined based on big data analysis. The allowable deviation is to provide a reasonable verification test range after comprehensively considering the differences. It can be set according to the actual situation or determined based on big data analysis.

[0022] As a possible implementation method, based on the mechanical matching verification information, the ECG activity data in the myocardial tissue measurement big data is extracted, and combined with the ECG activity information of the myocardial tissue bionic unit model, ECG activity matching analysis is performed to form ECG activity matching verification information, including: when the mechanical matching verification information is mechanical matching verification pass information, then the ECG measurement change function within the analysis period is formed according to the ECG activity data According to the ECG activity information of the myocardial tissue bionic unit model, the bionic ECG change function corresponding to the myocardial tissue bionic unit model during the analysis period is determined. ; According to the ECG measurement change function and bionic ECG function , perform ECG activity matching analysis and form ECG activity matching verification information.

[0023] In the present invention, the movement of myocardial tissue is mainly displayed through electrocardiogram data information. The contractility and mechanical verification tests basically determine that the bionic unit model of myocardial tissue has performance and functional integrity, while the continuous reliability of its movement work needs to be determined separately. By comparing and analyzing the digital model and the electrocardiogram data of the measured big data over a certain period of time, the verification test of the movement reliability can be accurately performed.

[0024] As a possible implementation method, according to the ECG measurement change function and bionic ECG function , perform ECG activity matching analysis to form ECG activity matching verification information, including: ECG measurement change function and bionic ECG function :If both , , then the ECG activity matching verification information is formed, is the allowed ECG variation deviation per unit time, W is the cumulative allowed ECG variation deviation, Indicates that it will obtain The maximum difference corresponding to all time points in the analysis period, T is the length of the analysis period; if not satisfied at the same time , , then the ECG activity matching verification failed information is generated.

[0025] In the present invention, for the reliability verification test based on ECG activity data, two aspects are mainly considered. One is the fluctuation difference of ECG data at each time point, which reflects whether the transient stability meets the requirements. The other is whether the cumulative difference in the total observation time, that is, the analysis period, exceeds the allowable amount, which reflects the cumulative effect of stability. Only when both requirements are met can it be determined that the myocardial tissue bionic unit model is reliable.

[0026] The beneficial effects of the testing method of the myocardial tissue bionic unit model provided by the present invention are:

[0027] This method obtains big data of myocardial tissue measurements to establish a digital myocardial tissue model for comparative verification testing with a myocardial tissue bionic unit model. The method also determines its performance and functionality in many aspects by matching and verifying the contractile performance, mechanical properties and electrocardiographic activity data of the myocardial tissue bionic unit model, effectively ensuring the performance of the myocardial tissue bionic unit model. At the same time, it also forms a systematic method for performance testing of the myocardial tissue bionic unit model, thereby improving the efficiency of performance verification testing of the myocardial tissue bionic unit model. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments of the present invention. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0029] Figure 1 A diagram showing the steps of a method for testing a myocardial tissue bionic unit model provided by an embodiment of the present invention;

[0030] Figure 2 A schematic structural diagram of a testing system for a myocardial tissue bionic unit model provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0031] The technical solutions in the embodiments of the present invention will be described below with reference to the accompanying drawings in the embodiments of the present invention.

[0032] With advancements in medical technology, treatments for heart diseases are becoming increasingly advanced and comprehensive. For cases where the myocardium is damaged and unable to recover functionally, it's possible to provide a bionic alternative that can achieve better myocardial function.

[0033] Currently, the development of bionic myocardial tissue models is becoming increasingly advanced, gradually producing model structures that can completely replace the entire myocardium's functions, providing the possibility of myocardial replacement. Given the different movements of myocardial tissue under normal circumstances, achieving its motion performance is relatively difficult. Furthermore, verifying the reliability and performance of the designed bionic myocardial tissue models has become a key challenge in the current research and development of bionic myocardial tissue models.

[0034] refer to Figure 1~Figure 2 The embodiment of the present invention provides a testing method for a myocardial tissue bionic unit model. The method obtains myocardial tissue measurement big data to establish a digital myocardial tissue model for comparative verification testing with the myocardial tissue bionic unit model, and through separate matching verification of the contractile performance, mechanical properties and electrocardiographic activity data of the myocardial tissue bionic unit model, determines its performance and functionality in multiple aspects, effectively guarantees the performance of the myocardial tissue bionic unit model, and also forms a systematic method for performance testing of the myocardial tissue bionic unit model, thereby improving the efficiency of performance verification testing of the myocardial tissue bionic unit model.

[0035] The testing method of the myocardial tissue bionic unit model specifically includes the following steps:

[0036] S1: Obtain big data on myocardial tissue measurements, extract myocardial tissue contractile performance test data and myocardial tissue scanning data, and establish a digital model of myocardial tissue based on contractile performance according to the myocardial tissue bionic unit model.

[0037] Acquire big data on myocardial tissue measurements, extract myocardial tissue contractile performance test data and myocardial tissue scanning data, and establish a myocardial tissue digital model based on contractile performance according to the myocardial tissue bionic unit model, including: establishing a basic digital model of myocardial tissue based on myocardial tissue scanning data and in combination with the myocardial tissue bionic unit model; performing feature extraction based on contractile performance according to the myocardial tissue contractile performance test data and in combination with the basic digital model of myocardial tissue to form model contractile performance characteristic data; using the model contractile performance characteristic data as a design indicator, perform model performance adjustment on the basic digital model of myocardial tissue based on secondary development to establish a digital model of myocardial tissue.

[0038] In order to establish a digital model of myocardial tissue that matches the myocardial tissue bionic unit model based on myocardial tissue measurement big data, three aspects need to be considered. One is the basic data of the model. The basic data here is the basic information required to generate the digital model, such as size, structure and other information. Based on this information, the digital model can be quickly established. The other is the performance data of the model. Considering that the performance of cardiac tissue is mainly obtained through its motion information, this application mainly considers establishing the corresponding model characteristic performance by obtaining contraction performance characteristic data.

[0039] A basic digital model of myocardial tissue is established based on myocardial tissue scanning data and in combination with a myocardial tissue bionic unit model, including: collecting size contour information of the myocardial tissue bionic unit model to form size contour feature information of a target model; using the size contour feature information of the target model as a reference, extracting matching scanning information corresponding to myocardial tissue whose size contour information in the myocardial tissue scanning data matches the size contour feature information of the target model, and determining the matched myocardial tissue as the matched myocardial tissue; determining the average basic parameter value of different basic model parameters based on all matching scanning information; and combining the target model size contour feature information and different average basic parameter values ​​to form a basic digital model of myocardial tissue.

[0040] The basic digital model of myocardial tissue primarily captures contour data on myocardial size and structure from measurement data. Considering that myocardial tissue is biological and exhibits certain individual differences, the bionic unit model of myocardial tissue inevitably has different applicability to different populations. Therefore, when establishing the basic digital model of myocardial tissue, the impact of individual differences on measurement data must be considered to avoid inaccurate results from subsequent validation tests caused by data that does not match the bionic unit model. Individual differences in myocardial tissue are primarily manifested in age; the size of myocardial tissue varies between individuals of different ages. Therefore, the dimensional contour feature information required for establishing the basic digital model of myocardial tissue is clustered and obtained using the dimensional contour feature information of the bionic unit model of myocardial tissue as a reference. This reference can encompass a certain range of dimensional contour feature information based on the bionic unit model of myocardial tissue, or it can be a single set of parameters. Once matching data is determined, the dimensional contour feature information of myocardial tissue from different individuals in the clustered measurement data can be extracted. Considering the certain volatility of feature information, the average of the different feature information is used as the input parameter for data model establishment to best adapt to the characteristics of the corresponding population. It should be noted that the size profile information can be obtained by providing scanning information in measurement big data, such as X-rays, nuclear magnetic resonance, etc., and other important parameter information such as average density can also be obtained.

[0041] Based on the myocardial tissue contractility test data and in combination with the basic digital model of myocardial tissue, contractility performance-based feature extraction is performed to form model contractility performance characteristic data, including: extracting different relevant contractility parameter values ​​in all matching myocardial tissues based on the myocardial tissue contractility test data, and clustering the different relevant contractility parameter values ​​to form different relevant contractility parameter sets; for different relevant contractility parameter sets, determining the corresponding average relevant contractility parameter values ​​and relevant contractility parameter ranges; and combining the different average relevant contractility parameter values ​​and the corresponding relevant contractility parameter ranges to form the model contractility performance characteristic data.

[0042] Myocardial contractility can be measured using parameters such as the rate of change of ventricular pressure, the slope of arterial pressure rise, ejection fraction, and isovolumetric contraction period. Therefore, when establishing array model performance characteristics for a basic digital model of myocardial tissue based on measurement data, data from different contractility parameters can be used as input. It should be noted that contractility primarily reflects the state and condition of myocardial tissue during exercise and is a comprehensive indicator of myocardial tissue performance. Therefore, basing the characterization of the basic digital model on contractility ensures that the resulting data model is fully characterized in terms of performance. Furthermore, due to the large volume of data, it is more appropriate to present the different contractility parameters obtained as average values. Corresponding parameter ranges are also provided to provide a reasonable adjustment range reference for considering the correlations between different contractility parameters during analysis, which may affect the adjustment of other contractility parameters when adjusting a single contractility parameter.

[0043] The method uses the model contraction performance characteristic data as the design index, performs model performance adjustment based on secondary development on the basic digital model of myocardial tissue, and establishes a digital model of myocardial tissue, including: using different average relevant contraction parameter values ​​as initial development and design targets, and using different relevant contraction parameter ranges as target allowable adjustment ranges, and performing the following secondary development model performance adjustment: performing secondary development on the basic digital model of myocardial tissue according to the initial development and design targets, and if the secondary development results match all the average relevant contraction parameter values, determining the model formed by the secondary development as the digital model of myocardial tissue; if the secondary development results do not match all the average relevant contraction parameter values, adjusting the unmatched average relevant contraction parameter values ​​within the corresponding target allowable adjustment range, so that the secondary development results match all the average relevant contraction parameter values, and determining the model formed by the secondary development as the digital model of myocardial tissue.

[0044] When a digital model is given functionality by shrinkage performance parameters, the parameter data cannot be directly implemented under the original or initial digital software or model parameters. Instead, it is necessary to use the digital software or model to carry out secondary development for the shrinkage performance parameters. This secondary development mainly establishes the relationship between the multiple adjustable basic parameters of the digital model and the shrinkage performance parameters, and then autonomously optimizes the design with the shrinkage performance parameters as the target. Since the correlation between the shrinkage performance itself will be reflected through the adjustable basic parameters, it is not necessarily reasonable to initially use the average value of different shrinkage performance parameters as input. Through the optimization process of secondary development, it can be determined whether the changes in the adjustable basic parameters can match all the shrinkage performance parameters. If they cannot match all, they can be adjusted based on the allowable adjustment range.

[0045] S2: Obtain the contractile performance parameters of the myocardial tissue bionic unit model, and perform contractility matching analysis in combination with the myocardial tissue digital model to form contractility matching verification information.

[0046] The contraction performance parameters of the myocardial tissue bionic unit model are obtained, and contractility matching analysis is performed in combination with the myocardial tissue digital model to form contractility matching verification information, including: setting the contraction matching allowable deviation corresponding to different contraction performance parameters, and determining the bionic contraction performance parameter values ​​of the different contraction performance parameters of the myocardial tissue bionic unit model; obtaining the model contraction performance parameter values ​​corresponding to different contraction performance parameters in the myocardial tissue digital model, and performing the following matching analysis in combination with the different bionic contraction performance parameter values ​​corresponding to the myocardial tissue bionic unit model: if for all contraction performance parameters, the difference between the bionic contraction performance parameter value and the corresponding model contraction performance parameter value does not exceed the corresponding contraction matching allowable deviation, contractility matching verification pass information is formed; if for all contraction performance parameters, the difference between the bionic contraction performance parameter value and the corresponding model contraction performance parameter value exceeds the corresponding contraction matching allowable deviation, contractility matching verification failure information is formed.

[0047] The digital myocardial tissue model, determined through secondary development, possesses contractile performance that matches big data, thus establishing comparative data that can be used for matching and verification testing with the bionic myocardial tissue unit model. The first verification test for the bionic myocardial tissue unit model is its contractile performance, which is a comprehensive reflection of its macroscopic nature. This matching takes into account the differences between the digital myocardial tissue model and the bionic myocardial tissue unit model. Therefore, the comparative verification test is controlled by an allowable deviation, which can be set based on actual conditions or determined through big data analysis.

[0048] S3: Based on the contractility matching verification information, the mechanical performance parameters of the myocardial tissue bionic unit model are obtained, and the mechanical performance matching analysis is performed in combination with the myocardial tissue digital model to form mechanical matching verification information.

[0049] According to the contractility matching verification information, the mechanical performance parameters of the myocardial tissue bionic unit model are obtained, and a mechanical performance matching analysis is performed in combination with the myocardial tissue digital model to form mechanical matching verification information, including: when the contractility matching verification information is contractility matching verification pass information, the bionic mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue bionic unit model are collected; the model mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue digital model are obtained, and a mechanical performance matching analysis is performed in combination with the bionic mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue bionic unit model to form mechanical matching verification information.

[0050] Myocardial tissue movement is a process of varying forces. Therefore, after confirming that contractility matching has been verified, a mechanical performance matching analysis is crucial to ensure that performance meets standards. This analysis can reflect the mechanical characteristics of the bionic myocardial tissue unit model. Of course, this matching analysis is performed using the data from the digital model's various mechanical performance parameters as a comparison.

[0051] Obtain the model mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue digital model, and perform mechanical performance matching analysis in combination with the bionic mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue bionic unit model to form mechanical matching verification information, including: determining the model mechanical comprehensive performance value corresponding to the myocardial tissue digital model based on the model mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue digital model ,in: , n is the number of different mechanical performance parameters, is an important contributing factor to the mechanical property parameter value numbered n, The model mechanical performance parameter value corresponding to the mechanical performance parameter numbered n; the bionic mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue bionic unit model are used to determine the bionic mechanical comprehensive performance value corresponding to the myocardial tissue bionic unit model ,in: , is the bionic mechanical performance parameter value corresponding to the mechanical performance parameter numbered n; the comprehensive mechanical performance value of the model and bionic mechanical comprehensive performance value :like , then the mechanical matching verification information is formed; if , then the mechanical matching verification fails. Allowable deviation for mechanical matching.

[0052] It should be noted that for the mechanical properties of the myocardial tissue bionic unit model, since mechanical parameters have inherent connections, such as stress and strain, and the transmission of force flow also has regularity and correlation with different structures, the verification test of mechanical properties is based on a comprehensive comparative analysis of the mechanical performance parameters under consideration. The important contribution factors reflect the importance of different mechanical performance parameters in the verification test or in the myocardial tissue on the movement of myocardial tissue. They can be set according to actual conditions or determined based on big data analysis. The allowable deviation provides a reasonable verification test range after comprehensively considering the differences. It can be set according to actual conditions or determined based on big data analysis.

[0053] S4: Based on the mechanical matching verification information, the ECG activity data in the myocardial tissue measurement big data is extracted, and combined with the ECG activity information of the myocardial tissue bionic unit model, ECG activity matching analysis is performed to form ECG activity matching verification information.

[0054] According to the mechanical matching verification information, the ECG activity data in the myocardial tissue measurement big data is extracted, and combined with the ECG activity information of the myocardial tissue bionic unit model, the ECG activity matching analysis is performed to form the ECG activity matching verification information, including: when the mechanical matching verification information is the mechanical matching verification pass information, the ECG measurement change function within the analysis period is formed according to the ECG activity data According to the ECG activity information of the myocardial tissue bionic unit model, the bionic ECG change function corresponding to the myocardial tissue bionic unit model during the analysis period is determined. ; According to the ECG measurement change function and bionic ECG function , perform ECG activity matching analysis and form ECG activity matching verification information.

[0055] The movement of myocardial tissue is mainly displayed through ECG data information. Through contractility and mechanical verification tests, it is basically determined that the bionic unit model of myocardial tissue has performance and functional integrity, while the continuous reliability of its movement work needs to be determined separately. By comparing and analyzing the digital model and the ECG data of the measured big data over a certain period of time, the verification test of movement reliability can be accurately performed.

[0056] According to the ECG measurement function and bionic ECG function , perform ECG activity matching analysis to form ECG activity matching verification information, including: ECG measurement change function and bionic ECG function :If both , , then the ECG activity matching verification information is formed, is the allowed ECG variation deviation per unit time, W is the cumulative allowed ECG variation deviation, Indicates that it will obtain The maximum difference corresponding to all time points in the analysis period, The duration of the analysis cycle; if not satisfied at the same time , , then the ECG activity matching verification failed information is generated.

[0057] For reliability verification tests based on ECG activity data, two aspects are mainly considered. One is the fluctuation difference of ECG data at each time point, which reflects whether the transient stability meets the requirements. The other is whether the cumulative difference in the total observation time, that is, the analysis period, exceeds the allowable amount, which reflects the cumulative effect of stability. Only when both requirements are met can the myocardial tissue bionic unit model be determined to be reliable.

[0058] The present invention also provides a testing system for a myocardial tissue bionic unit model, which includes: a data acquisition unit for acquiring big data on myocardial tissue measurements; a modeling unit for acquiring the big data on myocardial tissue measurements acquired by the data acquisition unit, and establishing a digital model of myocardial tissue in combination with the myocardial tissue bionic unit model; a verification and analysis unit for performing matching verification analysis on contractility, mechanical properties, and electrocardiographic activity data based on the digital model of myocardial tissue established by the modeling unit and in combination with the myocardial tissue bionic unit model, to form corresponding matching verification information.

[0059] In summary, the testing method of the myocardial tissue bionic unit model provided by the embodiment of the present invention has the following beneficial effects:

[0060] This method obtains big data of myocardial tissue measurements to establish a digital myocardial tissue model for comparative verification testing with a myocardial tissue bionic unit model. The method also determines its performance and functionality in many aspects by matching and verifying the contractile performance, mechanical properties and electrocardiographic activity data of the myocardial tissue bionic unit model, effectively ensuring the performance of the myocardial tissue bionic unit model. At the same time, it also forms a systematic method for performance testing of the myocardial tissue bionic unit model, thereby improving the efficiency of performance verification testing of the myocardial tissue bionic unit model.

[0061] In the embodiment of the present application, "indication" may include direct indication and indirect indication, and may also include explicit indication and implicit indication. The information indicated by a certain information is called information to be indicated. In the specific implementation process, there are many ways to indicate the information to be indicated, such as but not limited to, the information to be indicated can be directly indicated, such as the information to be indicated itself or the index of the information to be indicated. The information to be indicated can also be indirectly indicated by indicating other information, wherein there is an association relationship between the other information and the information to be indicated. It is also possible to indicate only a part of the information to be indicated, while the other parts of the information to be indicated are known or agreed in advance. For example, the indication of specific information can also be achieved by means of the arrangement order of each piece of information agreed in advance (such as specified in the protocol), thereby reducing the indication overhead to a certain extent. At the same time, the common parts of each piece of information can also be identified and indicated uniformly to reduce the indication overhead caused by indicating the same information separately.

[0062] In addition, the specific indication method can also be various existing indication methods, such as but not limited to the above-mentioned indication methods and various combinations thereof. The specific details of the various indication methods can be referred to the prior art and will not be repeated herein. As can be seen from the above, for example, when it is necessary to indicate multiple information of the same type, there may be a situation where the indication methods for different information are different. In the specific implementation process, the required indication method can be selected according to specific needs. The embodiment of the present application does not limit the selected indication method. In this way, the indication method involved in the embodiment of the present application should be understood to cover various methods that can enable the party to be indicated to obtain the information to be indicated.

[0063] It should be understood that the information to be indicated can be sent as a whole or divided into multiple sub-information and sent separately, and the sending period and / or sending time of these sub-information can be the same or different. The specific sending method is not limited in the embodiments of this application. The sending period and / or sending time of these sub-information can be predefined, for example, predefined according to a protocol, or can be configured by the transmitting device by sending configuration information to the receiving device.

[0064] "Pre-definition" or "pre-configuration" can be implemented by pre-saving corresponding codes, tables or other methods that can be used to indicate relevant information in the device, and the embodiments of the present application do not limit the specific implementation method. Among them, "saving" can mean saving in one or more memories. The one or more memories can be set separately or integrated in an encoder or decoder, a processor, or a communication device. The one or more memories can also be partially set separately and partially integrated in a decoder, a processor, or a communication device. The type of memory can be any form of storage medium, and the embodiments of the present application do not limit this.

[0065] The "protocol" involved in the embodiments of the present application may refer to a protocol family in the communication field, a standard protocol with a similar protocol family frame structure, or a related protocol used in future communication systems. The embodiments of the present application do not make specific limitations on this.

[0066] In the embodiments of the present application, descriptions such as "when...", "in the case of...", "if" and "if" all mean that the device will perform corresponding processing under certain objective circumstances. It does not limit the time, nor does it require the device to perform judgment actions when implemented, nor does it mean that there are other limitations.

[0067] In the description of the embodiments of this application, unless otherwise specified, " / " indicates that the associated objects are in an "or" relationship. For example, A / B can mean A or B. "And / or" in the embodiments of this application is merely a description of the associated relationship between the associated objects, indicating that three relationships can exist. For example, "A and / or B" can mean: A alone, A and B together, or B alone. A and B can be singular or plural. Furthermore, in the description of the embodiments of this application, unless otherwise specified, "multiple" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, "at least one of a, b, or c" can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or plural. Furthermore, to facilitate the clear description of the technical solutions of the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish between identical or similar items with substantially the same function or effect. Those skilled in the art will understand that words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not necessarily limit differences. At the same time, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or design. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete way for easy understanding.

[0068] It should be understood that the processor in the embodiments of the present application may be a central processing unit (CPU), but may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0069] It should also be understood that the memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0070] The above embodiments can be implemented in whole or in part via software, hardware (e.g., circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When loaded or executed on a computer, the processes or functions described in the embodiments of this application are fully or partially generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired means (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server or data center that contains a collection of one or more available media. The available medium can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0071] It should be understood that the term "and / or" as used herein simply describes a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A alone, A and B together, or B alone. A and B can be singular or plural. Furthermore, the character " / " as used herein generally indicates an "or" relationship between the associated objects, but it may also indicate an "and / or" relationship. For specific understanding, please refer to the context.

[0072] In this application, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, "at least one of a, b, or c" can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or plural.

[0073] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0074] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0075] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0076] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0077] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0078] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0079] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0080] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A method for testing a myocardial tissue bionic unit model, characterized in that: include: Acquire big data on myocardial tissue measurements, extract myocardial tissue contractility test data and myocardial tissue scanning data, and establish a digital model of myocardial tissue based on contractility performance according to the myocardial tissue bionic unit model; Acquiring contractile performance parameters of the myocardial tissue bionic unit model, and performing contractility matching analysis in combination with the myocardial tissue digital model to form contractility matching verification information; Acquiring mechanical performance parameters of the myocardial tissue bionic unit model based on the contractility matching verification information, and performing mechanical performance matching analysis in combination with the myocardial tissue digital model to generate mechanical matching verification information; Extracting electrocardiographic activity data from the myocardial tissue measurement big data based on the mechanical matching verification information, and performing electrocardiographic activity matching analysis in combination with the electrocardiographic activity information of the myocardial tissue bionic unit model to form electrocardiographic activity matching verification information; Among them, the myocardial tissue measurement big data is obtained, the myocardial tissue contraction performance test data and myocardial tissue scanning data are extracted, and a digital model of myocardial tissue based on contraction performance is established according to the myocardial tissue bionic unit model, including: Establishing a basic digital model of myocardial tissue based on the myocardial tissue scanning data and in combination with the myocardial tissue bionic unit model; Based on the myocardial tissue contractility test data and in combination with the myocardial tissue basic digital model, feature extraction based on contractility is performed to form model contractility feature data; Using the model contraction performance characteristic data as a design indicator, adjusting the model performance of the basic digital model of myocardial tissue based on secondary development to establish the digital model of myocardial tissue; According to the myocardial tissue scanning data and in combination with the myocardial tissue bionic unit model, a basic digital model of myocardial tissue is established, including: Collecting size profile information of the myocardial tissue bionic unit model to form size profile feature information of a target model; extracting matching scan information corresponding to myocardial tissue whose size contour information in the myocardial tissue scan data matches the size contour feature information of the target model with reference to the target model size contour feature information, and determining the matching myocardial tissue as the matching myocardial tissue; Determining average basic parameter values ​​of different basic model parameters based on all the matching scan information; The target model size contour feature information and different average basic parameter values ​​are combined to form the myocardial tissue basic digital model; The method of extracting features based on contraction performance according to the myocardial tissue contraction performance test data and combining the myocardial tissue basic digital model to form model contraction performance feature data includes: Extracting different relevant contraction parameter values ​​in all the matching myocardial tissues according to the myocardial tissue contractility test data, and clustering the different relevant contraction parameter values ​​to form different relevant contraction parameter sets; For different sets of the relevant shrinkage parameters, determining corresponding average relevant shrinkage parameter values ​​and relevant shrinkage parameter ranges; Collecting different average relevant shrinkage parameter values ​​and corresponding relevant shrinkage parameter ranges to form the model shrinkage performance characteristic data; The method of adjusting the model performance of the basic digital model of myocardial tissue based on secondary development by using the model contraction performance characteristic data as a design indicator to establish the digital model of myocardial tissue includes: For the basic digital model of myocardial tissue, different average related contraction parameter values ​​are used as initial development and design targets, and different related contraction parameter ranges are used as target allowable adjustment ranges, and the following secondary development model performance adjustment is performed: performing secondary development on the basic digital model of myocardial tissue according to the initial development design goal, and determining the model formed by the secondary development as the digital model of myocardial tissue if the secondary development result matches all the average relevant contraction parameter values; If the secondary development result does not match all the average relevant contraction parameter values, the unmatched average relevant contraction parameter values ​​are adjusted within the corresponding target allowable adjustment range so that the secondary development result matches all the average relevant contraction parameter values, and the model formed by the secondary development is determined as the digital model of myocardial tissue.

2. The method for testing the myocardial tissue bionic unit model according to claim 1, characterized in that: The step of obtaining the contractile performance parameters of the myocardial tissue bionic unit model and performing contractile matching analysis in combination with the myocardial tissue digital model to form contractile matching verification information includes: Setting contraction matching allowable deviations corresponding to different contraction performance parameters, and determining bionic contraction performance parameter values ​​of the myocardial tissue bionic unit model for different contraction performance parameters; Obtain the model contraction performance parameter values ​​corresponding to different contraction performance parameters in the myocardial tissue digital model, and perform the following matching analysis in combination with the different bionic contraction performance parameter values ​​corresponding to the myocardial tissue bionic unit model: If for all the contraction performance parameters, the differences between the bionic contraction performance parameter values ​​and the corresponding model contraction performance parameter values ​​do not exceed the corresponding contraction matching allowable deviations, contraction matching verification pass information is generated; If, for all the contraction performance parameters, the difference between the bionic contraction performance parameter value and the corresponding model contraction performance parameter value exceeds the corresponding contraction matching allowable deviation, a contraction matching verification failure message is generated.

3. The method for testing the myocardial tissue bionic unit model according to claim 2, wherein: The step of obtaining the mechanical performance parameters of the myocardial tissue bionic unit model based on the contractility matching verification information and performing mechanical performance matching analysis in combination with the myocardial tissue digital model to form mechanical matching verification information includes: When the contractility matching verification information is the contractility matching verification pass information, collecting bionic mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue bionic unit model; The model mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue digital model are obtained, and the mechanical performance matching analysis is performed in combination with the bionic mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue bionic unit model to form the mechanical matching verification information.

4. The method for testing the myocardial tissue bionic unit model according to claim 3, characterized in that: The obtaining of model mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue digital model, and performing mechanical performance matching analysis in combination with the bionic mechanical performance parameter values ​​corresponding to different mechanical performance parameters of the myocardial tissue bionic unit model to form the mechanical matching verification information includes: The model mechanical performance parameter values ​​corresponding to the different mechanical performance parameters of the myocardial tissue digital model are used to determine the model mechanical comprehensive performance value corresponding to the myocardial tissue digital model. in: n is the number of the different mechanical performance parameters, α n is an important contributing factor to the mechanical property parameter value numbered n, a n is the model mechanical property parameter value corresponding to the mechanical property parameter numbered n; The bionic mechanical performance parameter values ​​corresponding to the different mechanical performance parameters of the myocardial tissue bionic unit model are used to determine the bionic mechanical comprehensive performance value corresponding to the myocardial tissue bionic unit model. in: b n is the bionic mechanical performance parameter value corresponding to the mechanical performance parameter numbered n; The comprehensive mechanical performance value of the model and the biomimetic mechanical comprehensive performance value like Then the mechanical matching verification pass information is formed; like This forms the information that the mechanical matching verification has failed, and β is the allowable deviation of the mechanical matching.

5. The method for testing the myocardial tissue bionic unit model according to claim 4, characterized in that: The extracting of electrocardiographic activity data from the myocardial tissue measurement big data based on the mechanical matching verification information and combining the electrocardiographic activity information of the myocardial tissue bionic unit model to perform electrocardiographic activity matching analysis to form electrocardiographic activity matching verification information includes: When the mechanical matching verification information is the mechanical matching verification pass information, an electrocardiogram measurement change function F is formed within the analysis period according to the electrocardiogram activity data. mean (t); According to the electrocardiographic activity information of the myocardial tissue bionic unit model, the bionic electrocardiographic change function F corresponding to the myocardial tissue bionic unit model in the analysis period is determined. bio (t); According to the electrocardiographic measurement variation function F mean (t) and the bionic ECG change function F bio (t) Performing electrocardiographic activity matching analysis to generate electrocardiographic activity matching verification information.

6. The method for testing the myocardial tissue bionic unit model according to claim 5, characterized in that: The electrocardiogram measurement change function F mean (t) and the bionic ECG change function F bio (t) performing electrocardiographic activity matching analysis to generate electrocardiographic activity matching verification information, including: The electrocardiogram measurement change function F mean (t) and the bionic ECG change function F bio (t): If INT(F mean (t)-F bio (t))≤γ, Then the ECG activity matching verification information is formed, γ is the allowed ECG change deviation per unit time, W is the cumulative allowed ECG change deviation, INT(F mean (t)-F bio (t)) indicates that F mean (t)-F bio (t) the maximum difference corresponding to all time points within the analysis period, where T is the duration of the analysis period; If INT(F mean (t)-F bio (t))≤γ, This generates information indicating that the ECG activity matching verification has failed.

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